Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/26050
Title: Zonotopic distributed fusion for nonlinear networked systems with bit rate constraint
Authors: Zhao, Z
Wang, Z
Zou, L
Chen, Y
Sheng, W
Keywords: nonlinear networked systems;distributed fusion;bit rate constraint;set-membership state estimation;zonotopes
Issue Date: 21-Sep-2022
Publisher: Elsevier
Citation: Zhao, Z. et al. (2022) 'Zonotopic distributed fusion for nonlinear networked systems with bit rate constraint', Information Fusion, 90, pp. 174 - 184. doi: 10.1016/j.inffus.2022.09.014.
Abstract: In this paper, the distributed fusion estimation problem is studied for a class of nonlinear networked systems subject to unknown-but-bounded (UBB) noises. A bit rate constraint is introduced to quantify the limited bandwidth of the communication channel, under which a bit rate allocation protocol is further designed by solving a certain off-line optimization problem. Based on the received data from the network, several local extended-Kalman-type estimators are constructed and zonotopic sets confining local estimation errors are then obtained. By designing the local estimator parameters, the -radii of the obtained zonotopic sets are minimized. Subsequently, with the calculated local estimates and zonotopic sets, a zonotopes-based distributed fusion estimator is put forward by means of the matrix-weighted fusion method, and the global zonotope (i.e., the zonotope encompassing the error between the system state and the fused estimate) is derived. Moreover, under the proposed zonotopes-based fusion framework, the distributed fusion estimators are designed based on, respectively, the scalar-weighted fusion method and the diagonal-matrix-weighted fusion method. Finally, the effectiveness of the proposed distributed fusion method is illustrated through a numerical example.
Description: Data availability: Data will be made available on request.
URI: https://bura.brunel.ac.uk/handle/2438/26050
DOI: https://doi.org/10.1016/j.inffus.2022.09.014
ISSN: 1566-2535
Other Identifiers: ORCID iDs: Zidong Wang https://orcid.org/0000-0002-9576-7401; Lei Zou https://orcid.org/0000-0002-0409-7941.
Appears in Collections:Dept of Computer Science Embargoed Research Papers

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